Mass spectrometry analysis of gut tissue in acute SIV-infection in rhesus macaques identifies early proteome alterations preceding the interferon inflammatory response

HIV infection damages the gut mucosa leading to chronic immune activation, increased morbidities and mortality, and antiretroviral therapies, do not completely ameliorate mucosal dysfunction. Understanding early molecular changes in acute infection may identify new biomarkers underlying gut dysfunction. Here we utilized a proteomics approach, coupled with flow cytometry, to characterize early molecular and immunological alterations during acute SIV infection in gut tissue of rhesus macaques. Gut tissue biopsies were obtained at 2 times pre-infection and 4 times post-infection from 6 macaques. The tissue proteome was analyzed by mass spectrometry, and immune cell populations in tissue and blood by flow cytometry. Significant proteome changes (p < 0.05) occurred at 3 days post-infection (dpi) (13.0%), 14 dpi (13.7%), 28 dpi (16.9%) and 63 dpi (14.8%). At 3 dpi, proteome changes included cellular structural activity, barrier integrity, and activation of epithelial to mesenchymal transition (EMT) (FDR < 0.0001) prior to the antiviral response at 14 dpi (IFNa/g pathways, p < 0.001). Novel EMT proteomic biomarkers (keratins 2, 6A and 20, collagen 12A1, desmoplakin) and inflammatory biomarkers (PSMB9, FGL2) were associated with early infection and barrier dysfunction. These findings identify new biomarkers preceding inflammation in SIV infection involved with EMT activation. This warrants further investigation of the role of these biomarkers in chronic infection, mucosal inflammation, and disease pathogenesis of HIV.


Proteomic analysis of acute SIV infection.
We performed cluster analysis of proteins significantly altered post-infection in colon and rectal tissue, showing distinct temporal changes in both compartments (Fig. 3). In the colon, pathway analysis indicated that proteins related to cell-to-cell adhesion were significantly altered (adj.p = 0.0005) as early as 3 dpi (Fig. 3a). By 14 dpi, during peak viremia, activation of IFN (adj.p = 2.63E−6) and response to virus (adj.p = 1.35E−4) pathways were observed. A similar activation of the IFN signaling pathway was also observed in rectal tissue by 14 dpi (Fig. 3c, p = 9.43E−11). Gene set enrichment analysis (GSEA) performed on data from both compartments showed an increase in IFN responses by 14 dpi (FDR < 0.0005), which continued up to 63 dpi (Fig. 3b,d). The colon showed a stronger proteome response to infection on 3 dpi in comparison to the rectum (Fig. 3b). Mitochondrial functions (oxidative phosphorylation, fatty acid metabolism) were decreased (adj.p < 0.05) early in the colon and later in the rectum. However, only www.nature.com/scientificreports/ 26-29% of the proteins involved in these pathways overlapped between intestinal compartments. Interestingly, myogenesis (adj.p = 0.0008) and epithelial to mesenchymal transition (EMT) (adj.p < 0.0001) pathways were increased at 3 dpi in the colon. The interferon response has been widely studied in the context of both SIV 10 and HIV infection 11 . HIV is known to trigger IFN-I by innate immune sensors, eliciting broad anti-viral effects through interferon-simulated genes 12 . However, a complete proteome characterization of the IFN response to SIV/HIV infection has not been previously described. Using GSEA analysis, we identified 17 (colon) and 11 (rectal)  ). Proteasome Activator Subunit 2 (PSME2) has been identified in a gene expression analysis in HIV-associated neurocognitive disorder, but has no known role in HIV pathogenesis 13 . Both Proteasome 20S Subunit Beta 9 (PSMB9, immunoproteasome) and Fibrinogen Like 2 (FGL2) are novel proteins identified in the context of HIV infection. Over expression of FGL2 has prothrombinase activity and is known to induce EMT 14 .
We next compared the relationship between IFN-proteome changes to the cellular immune response. This included a correlation analysis between protein abundance and the percentage of immune cell populations (Fig. 4). Activated CD4+ and CD8+ T cells, as a percentage of total CD4+ and CD8+ T cells, were positively associated with the IFN-proteome signature in all compartments including the blood, colon, and lymph node. Total CD4+ T-cells, Th17 cells, and Th22 cells negatively associated with IFN-proteome signature, more pronounced in the colon and rectum, consistent with the depletion kinetics of CD4+ T cells during SIV infection 15 . Neutrophil infiltration into infected mucosal tissues is a hallmark of the innate immune response 16 , and while blood neutrophils (measured as a percentage of total CD45+ cells) negatively associated with the IFN-proteome signature there were no associations to mucosal neutrophils. However, as we did not measure other neutrophil markers we could not make further comparisons to neutrophil phenotype or activation status.
Epithelial to mesenchymal transition (EMT) is a transient process where epithelial cells transition to mesenchymal cells either partially or fully, and is characterized mostly by a structural/phenotypical change of the cell 17 . A metastable cell having both epithelial and mesenchymal traits has been observed in some studies, and highlights the plasticity of the process 18 . EMT is observed during wound healing, when morphological changes to the epithelial cells is needed to allow migration of cells across the wound for closure. However, unchecked EMT processes can lead to fibrotic diseases, inflammatory diseases, and cancer 18 . During EMT there is a loss in epithelial markers including cell-cell junctions and a reorganization of cellular cytoskeleton structure. The amount of reorganization differs depending on the extent of change and tissue cell type. Certain protein expression patterns, such as the decrease in classical epithelial markers E-cadherin, claudins, occludin, desmoplakin and keratins as well as an increase in mesenchymal markers collagens, N-cadherin and fibronectin, are classical phenotypical changes during this process 18 . www.nature.com/scientificreports/ In this study, we found both mesenchymal and epithelial markers, as well as signaling proteins that induce EMT, significantly altered in colon, but not rectal, tissues at 3 dpi (  www.nature.com/scientificreports/ cells change from an epithelial to a mesenchymal state. At 14 dpi, many epithelial markers were decreased in comparison to baseline (Fig. 5b) including E-cadherin (CDH1), Desmoplakin (DSP), and many keratins. A decrease of E-cadherin is the prototypical signature of EMT 19 . There was no similar EMT signature observed in the rectal tissues.

Associations of EMT and IFN signatures during acute SIV.
Soluble epithelial dysfunction biomarkers were measured in the blood, including zonulin and lipopolysaccharide binding protein (LBP). A breakdown in the intestinal barrier releases zonulin into the bloodstream and is a biomarker of diseases such as diabetes, celiac disease and obesity. Measuring LBP is an indirect method of determining microbial translocation and is used to describe sepsis. Interestingly, we did not observe a correlation with most of the epithelial or mesenchymal proteins and zonulin in either the colon or the rectal tissues ( Supplementary Figs. 3, and 4). It may be that Neutrophils are thought to infiltrate tissues and cause barrier damage during clearance of infections 20 . In previous studies, neutrophils have been shown to contribute to the activation of EMT and can promote tumor migration through IL17a 21 . Neutrophils in the blood positively correlated with epithelial keratins 13, 3, 4, 5 and 6A ( Supplementary Fig. 3a) but had no correlation to EMT markers in the colon tissues.
As T-cells play a large role in HIV infection, levels of CD4+ T-cells (including Th17 and Th22 cells) in the blood, colon and lymph nodes were measured, along with activation (HLADR) and proliferation (Ki67) markers. Th17 cells have well characterized roles in both immune pathology as well as maintaining homeostasis at mucosal barrier sites. Th22 cells also enhance immune responses to pathogen infection while promoting repair of damaged epithelial barriers 22 . In our study, Th17 cells in both the colon and blood, and Th22 cells in the colon, were seen to have a positive correlation with keratin expression in colon tissue. Like neutrophils, Th17s produce IL17 and may induce EMT expression. However, a decrease in Th17 cells after infection and a negative correlation with IL17 and colon markers of EMT ( Supplementary Fig. 3c), suggests that Th17 cells do no activate EMT in this context.
CD4+ T-cells are targets for HIV infection and a decrease in total CD4+ T-cell counts is a hallmark of HIV infection, which we observed in our study. Colon tissue epithelial markers were positively correlated with the amount of both systemic and mucosal CD4+ T-cells, with more biomarkers associating with CD4+ T-cells in the lymph node (15 proteins) in comparison to both the colon and blood CD4+ T-cells (12 and 7 proteins, respectively). Conversely, the activation and proliferation of T-cells were negatively correlated with epithelial markers, as CD4+ and CD8+ T-cells were activated and started proliferating after infection. A stronger systemic rather than local association with T-cells and epithelial markers was observed, with more proteins correlating to activation and proliferation of T-cells in the lymph node than in the colon (Supplementary Fig. 3). In contrast to the colon, there were very few significant correlations (Keratin 1, KRT1; Keratin 20, KRT20; Plakophilin 2 PKP2) between EMT proteins in the rectal tissues and immune cell abundance or activation (Supplementary Fig. 4). Few mesenchymal or EMT activation signaling proteins were correlated with immune cells, as EMT initiated earlier (3 dpi) than the immune response (14 dpi).
Peak viral load (PVL) during acute HIV infection is associated with the amount of time it takes to progress to AIDS and is therefore a strong marker of pathogenesis. Colon epithelial proteins were inversely correlated with viral load, decreasing by 14 dpi when peak viremia occurred (Supplementary Fig. 3). However mesenchymal markers which started increasing at 3 dpi did not correlate with viral load, indicating that the onset of EMT, characterized by an increase in mesenchymal markers, occurred prior to viral peak. We further explored the relationship between both EMT and IFN proteome alterations and viral load. We used the LASSO algorithm (Least Absolute Shrinkage and Selection Operator) with supervised cross validation by PLSR (Partial Least-Squares Regression) to evaluate the relationship between either EMT or IFN, and viral load. www.nature.com/scientificreports/ For the EMT signature, changes in the expression of certain epithelial and mesenchymal proteins after 3 dpi were able to predict PVL with moderate accuracy of 75% (Fig. 6a), (R2 = 0.754, MSEP = 20.8%, variance explained on PLS component 1 = 51.6%). A total of 5 EMT factors were selected in the model, including Keratin 6a (KRT6a) which was highlighted in Fig. 4 to significantly decrease after infection. Other epithelial and mesenchymal markers selected included KRT2, KRT20, COL12A1, and DSP. Together, this indicated a moderate predictive relationship between the degree of changes in EMT proteins early in SIV infection and peak viral load at 14 dpi.
For the IFN signature, changes in the expression of certain interferon proteins after 3 dpi were able to predict PVL with an accuracy of 93% (Fig. 6b), (R2 = 0.93, MSEP = 43.9%, variance explained on PLS component 1 = 35.9%). A total of 6 IFN factors were selected in the model, including GSEA identified IFN proteins PSMB9 and CD38, as well as NUP93, PSMA2, PSMA3 and STAT3. These proteins indicated a good predictive relationship between the initial IFN proteome response and peak viral load.

Discussion
During acute HIV infection, the gastrointestinal tract is a major site of HIV replication leading to substantial depletion of lamina propria CD4+ T cells 23 . With treatment, there is a suppression of viral replication and a partial restoration of CD4+ T cells, but epithelial barrier damage that occurs due to HIV infection persists 24 . In this study, to the best of our knowledge, we identified new biomarkers of early SIV infection which related to www.nature.com/scientificreports/ EMT activation signaling and mesenchymal biomarkers at 3 dpi (BGN, CALD1, DCN, LRP1, LUM, PLOD3, SCG2, TGFb1, TGM2 and TNC). This was followed by a decrease in epithelial biomarkers at 14 dpi which was associated with the depletion of CD4+ T cells as well as immune cell activation and viral load. In addition, this analysis identified new proteins involved in the antiviral immune response (PSMB9 and FGL2) during peak viral load. Collectively this information adds to our understanding of HIV infection by identifying new proteome biomarker changes in early infection related to structural epithelial barrier integrity, which may be important for severity of disease progression and immune activation. Neutrophils, the first responders during infection, help control pathogenic infections by triggering an inflammatory response, but also damage tissue due to the release of reactive oxygen species (ROS), proteases or other harmful molecules 25 . In our study, peripheral neutrophils negatively associated with protein markers of EMT and IFN response in the colon tissue. However, mucosal neutrophils were not associated with these signatures. Our previous analysis showed that neutrophils did not infiltrate the tissues after infection 6 , therefore an association was not expected. However, neither neutrophil function (such as releasing ROS) nor phenotype was captured in our assays and it is possible these relationships may be important and a future area of investigation.
The EMT process is characterized by the disassembly of epithelial cell-cell contacts and a loss of polarity 17 to provide epithelial cells plasticity and a motile mesenchymal phenotype 26 . The repression of these epithelial genes and restructuring of the cells are simultaneously coupled to activation of mesenchymal genes, such as vimentin, N-cadherin and collagens 17 to enable this process. EMT is essential for tissue development as well as wound healing, and the reverse process, mesenchymal-to-epithelial transition (MET), is important for final development of cellular differentiation 27 . Though a transient EMT response is essential for the wound healing process allowing for re-epithelialization and extracellular matrix remodeling, unchecked or sustained EMT activation leads to a pathologic wounding response causing tissue fibrosis, inflammation and even cancer metastasis. It has been shown that a continued EMT response occurs through inflammation, specifically IFN 28 , leading to eventual organ destruction. For example, the intestinal fibrosis observed during inflammatory bowel diseases (IBD) is considered the final outcome of the host reaction to persistent inflammation 29 and occurs through EMT. Our results from this study indicate that follow up studies targeting MET may be warranted as avenues of research to augment treatment regimens such as ART to aid in wound healing from gut disfunction.
It has been previously shown that HIV infection causes EMT in the kidneys of a mouse model, leading to HIV-associated nephropathy and compromised barrier function 30 . As well, a recent paper has shown that HIV-1 proteins gp120 and tat were able to induce EMT in oral and genital mucosal cells in vitro 31 . EMT has been proposed as a mechanism of HIV-induced carcinogenesis in mice 32 , and has been recently proposed to play a role in the sequestration of virions in mucosal epithelial cells 33 . Whether HIV can induce this pathway in intestinal cells by direct viral-host interaction in humans, or if EMT can influence HIV pathogenesis, has yet to be studied. Wound healing ability in African green monkeys has been recently shown to contribute to SIV pathogenesis control 8 , indicating that unchecked or absent wound healing processes may underlie SIV and HIV pathogenesis that is observed in rhesus macaques and humans, respectively.
In the context of acute wound healing and inflammatory injury, EMT is triggered by numerous growth factors, chemokines and MMPs 34 . Interferons, in particular have been linked to EMT activation in the context of cancer 35 and both TNFa and IFNg have both shown to induce EMT in vitro 36 . The roles of IFN in HIV infection have been extensively studied, and evidence to support a link between a continued IFN response and HIV pathogenesis has been discovered by investigating mechanisms by which natural monkey hosts do not develop AIDS 37,38 . Our proteome analysis of SIV-infected rhesus macaques showed IFN was activated in both colon and rectal tissues after infection correlating with peak viral load. Many proteins encoded by interferon-stimulated genes that we identified have been previously observed in HIV infection including STAT1, MX1, MX2, OAS2, however, PSMB9 and FGL2 are novel. PSMB9 contributes to autoinflammatory syndromes caused by loss of function mutations and accompanied by a type I interferon signature 39 . FGL2 has been identified as a novel effector molecule of Treg cells playing a critical role in innate and adaptive immunity 40 . The functions of these novel proteins warrant further investigation to a possible role in IFN-related HIV pathogenesis.
The limitation of this study was the use of a small animal group and the inability to collect samples from a control group (one with no SIV infection). Without a mock challenge we are limited in determining how repeated sedation and biopsies may have impacted the data. However, we have tried to improve on this limitation by collecting multiple baseline timepoints and averaging the results for our analysis. Furthermore, proteomic analysis was restricted to whole tissue and thus contributions of these changes to different cell populations was restricted to correlative analyses.
Our results indicate that a more activated CD4+ and CD8+ T cell environment, in addition to a loss in barrier integrity through EMT activation, could lead to an increase in viral load since more viral particles may be able to penetrate the 'leaky' tissues and reach activated target T-cells. As well, immune cells and cells expressing a more mesenchymal phenotype have been shown to reciprocally activate each other in tumor cells 41 . These events could exacerbate the known vicious cycle of HIV pathogenic events in the gut tissue, where barrier damage leads to systemic exposure to gut microbial products and increasing T-cell activation.
In conclusion, this analysis has identified new biomarkers of early SIV infection in the gut tissue proteome related to EMT activation, the IFN response, immune activation and inflammation. This provides further data on early protein biomarkers and pathways that may be important for contributing mechanisms for HIV infection and pathogenesis. In the case of HIV infection, follow-up research on the relationship and role of these biomarkers in HIV pathogenesis is warranted to determine if these proteins are contributors to disease pathogenesis in chronic HIV infection.

Methods
Study animals. Animals were housed and cared for in Association for the Assessment and Accreditation of Laboratory Animal Care international (AAALACi) accredited facilities, and all animal procedures, methods, and experimental protocols were performed according to protocols approved by the Institutional Animal Care and Use Committee (IACUC) of University of Washington. All methods were carried out in accordance with relevant guidelines and regulations. All methods are reported in accordance with ARRIVE guidelines for the reporting of animal experiments. Six adult male rhesus macaques (Macaca mulatta) were infected intrarectally with 100,000 TCID50 SIV MAC239x . Baseline samples for blood, lymph node, rectal and colon biopsies were taken 56-and 21-days pre-infection (for control samples), and 3, 14, 28 and 63 days post-infection as previously described 42 (Fig. 1). Viral loads were determined by real-time reverse transcription (RT)-PCR using primers specific for SIVgag as previously described 43 . ELISAs were read using an iMark Microplate Reader (Biorad, Hercules, CA). Animals were euthanized as per the protocol-specified experimental endpoint between 101 and 141 days post-infection.
Sample preparation for mass spectrometry. Proteins were extracted from frozen colon biopsies as previously described 44 . Frozen tissue samples were homogenized, centrifuged, and digested for mass spectrometry as previously described 44  Statistical analysis. Normalized protein abundance values were generated with Progenesis, outliers with a median normalized abundance greater than one standard deviation removed. Proteins with high technical variance among standards (Coefficient of variance > 25%) were removed from downstream analysis. Protein differences were determined using paired, non-parametric Mann-Whitney tests, comparing average baseline values to each time point post-infection (3, 14, 28, 63 dpi). Multiple hypothesis testing correction was performed using the Benjimani-Hochberg method (false discovery rate, FDR = 5%). Hierarchical cluster analysis (NMF package in R v3.6.1) was performed on proteins differentially abundant at any time point, using Spearman rank correlation as the distance metric. Differentially regulated proteins were used to characterize top biological pathways and functions altered during acute infection, using both DAVID (Database for Annotation, Visualization, and Integrated Discovery, v6.8) and IPA (Ingenuity® Pathway Analysis) software. Multivariate models were performed to determine a minimum EMT/IFN protein signature needed to distinguish indicating variables of SIV pathogenesis: peak viral load (14 dpi). Models were constructed using the LASSO method for regression shrinkage and selection using glmnet in R (K-fold cross validation). PLSR assessed the ability of LASSO features describe variance in either peak viral load using fivefold cross-validation repeated 50 times with 2 components selected after tuning, according to the MixOmics package in R (mixOmics v6.6.2). Model fit (R2), mean squared error of prediction (MSEP) and variance explained along PLS components were used to assess predictive ability of the models. Principal component (PC) analysis of normalized LASSO markers was performed using the base package in R.
Flow cytometry analysis. Flow cytometry staining and analysis was performed as previously described, including the full gating strategy used for this analysis 6 . Briefly, samples were stained with LIVE/DEAD Fixable Aqua Dead Cell Stain (ThermoFisher) and stained with surface antigen markers, or intracellular cytokine staining was performed with permeabilization using Cytofix/Cytoperm (BD Biosciences). Stained samples were fixed in 1% paraformaldehyde and collected on a LSR II (BD Biosciences, La Jolla, CA). Analysis was performed in FlowJo (version 9.7.6, Treestar Inc., Ashland, OR). Neutrophils and CD4+ T cells were measured as a percentage of total CD45 cells. Th17 and Th22 cells were measured as a percentage of total CD4+ T cells. HLA-DR+ and Ki67+ cells were measured as a percentage of total CD4+ or CD8+ cells.

Data availability
All data generated and/or analyzed during the current study are provided as supplementary information files.